Vertmax duo use on overseeded perennial ryegrass

‘Elicitors of Plant Response (EPR) Trial on perennial ryegrass
var Stellar 3G. Trial examining the impact on growth rate, root
development and abiotic stress tolerance of EPR (salicylic acid,
copper pthalamine and 6 benylaminopurine (BAP)) on
perennial ryegrass:’
Jerry Spencer BSc Hons Grad Dip Gilba Solutions Pty Ltd
08/02/2020
Abstract
Synthetic pesticides have allowed growers to dramatically increase crop yield and quality.
However, these compounds are often toxic and their overuse has led to pathogen resistance
[Schreinemachers and Tipraqsa, 2012; Lucas, Hawkins and Fraaije, 2014). An
environmentally friendlier strategy for reducing crop loss involves regulating SAR
(daRocha, Hammerschmidt 2005).
Discussion of Results
Vertmax® Duo throughout the entire trial gave significantly earlier seed germination and
growth following application compared to several other treatments when applied at 1L/Ha.
This means it offers a useful aid in relation to encouraging more rapid and successful
establishment of warm season turf areas overseeded with ryegrass in the autumn and also
in those areas comprising standalone perennial ryegrass swards.
Vertmax® Duo also gave significantly greater root growth compared to the other
treatments following application at 1L/Ha. This offers the turf manager a means of actively
encouraging root growth of perennial ryegrass following application, leading to a turf cover
better able to manage wear and stress such as drought.
On all measured criteria relating to root growth perennial ryegrass treated with Vertmax®
Duo compared to the control gave:
• A significantly higher root volume
• Significantly longer roots
• Significantly greater individual root width
• A significantly greater root depth
• After 42C for 24 hours a significantly greater root length (+22% over the control).

Background to Treatments
Plants possess a range of defences that can be actively expressed in response to biotic and
abiotic stresses. The timing of these defence responses is critical and can be the difference
between being able to cope or succumbing to the challenge of a pathogen or n abiotic stress
such a drought. Systemic acquired resistance (SAR) and induced systemic resistance (ISR)
are two forms of induced resistance; in both SAR and ISR, plant defences are
preconditioned by prior infection or treatment that results in resistance (or tolerance)
against subsequent challenge by a pathogen or parasite. Great strides have been made over
the past 20 yr in understanding the physiological and biochemical basis of SAR and ISR.
Much of this knowledge is due to the identification of a number of chemical and biological
elicitors, some of which are commercially available for use in conventional agriculture.
However,the effectiveness of these elicitors to induce SAR and ISR as a practical means to
control various plant diseases is just being realized. Stimulating the natural plant immunity
through induced resistance is among those strategies. Upon infection, the plants are able to
fight against pathogen attacks by activating their immune mechanisms
The classic form of SAR can be triggered by exposing the plant to virulent, avirulent, and
nonpathogenic microbes, or artificially with chemicals such as salicylic acid (SA), 2,6-
dichloro-isonicotinic acid (INA) or benzo (1,2,3) thiadiazole- 7-carbothioic acid S-methyl
ester (BTH) (reviewed in Sticher et al., 1997).
BTH and INA are by far the best studied chemical elicitors available; both are considered
functional analogs of salicylic acid, and elicit a systemic form of induced resistance across a
broad range of plant–pathogen interactions (Friedrich et al., 1996). BTH (also known as
acibenzolar-S-methyl or ASM) is distributed by Syngenta Crop Protection (Raleigh, NC,
USA; formerly Novartis Crop Protection) as Actigard® and as Daconil Action® in the USA
and Bion® in Europe.Two other commercially available products overseas are Civitas®
and Harmonizer®.
ASM belongs to a product category called Host Plant Defense Induction (FRAC GROUP P).
The Host Plant Defense Induction group has no direct toxic effect against pathogenic fungi
and bacteria; instead, ASM triggers the natural defense response or the Systemic Acquired
Resistance of the turfgrass by activating the production of pathogenesis-related (PR)
proteins.
Defense activators such as Actigard®, Civitas®, and other newly developed compounds are
known to decrease severity of turfgrass diseases in Agrostis species (Cortes-Barco AM,
Hsiang T, Goodwin PH. 2010. and Hsiang T, Goodwin PH, Cortes-Barco AM. 2011) . The
mode of action for most of these activators is SAR (systemic acquired resistance), mediated
by the salicylic acid pathway, or ISR (induced systemic resistance), mediated by jasmonic
acid or ethylene related pathways. However, some defense activators work via pathways
that are not fully characterized. Because these chemicals work through plant defense gene
expression of the host, the plant genotype (cultivar) can have a major impact on their
effectiveness. The effect of plant genotype on defense gene expression has not been clearly
elucidated in Agrostis species or other turfgrass species. In some preliminary work,

differences have been found between cultivars of Agrostis species in their ability for
disease resistance induction by some of these compounds.
As discussed earlier Acibenzolar-S-methyl (ASM), a synthetic functional analog of salicylic
acid, can induce systemic acquired resistance in plants, but its effects on abiotic stress
tolerance is not well known. Jesperson, D., Yu, J. and Huang, B., 2017 examined the effects of
acibenzolar-S-methyl on heat or drought tolerance in creeping bentgrass (cv. ‘Penncross’)
(Agrostis stolonifera). These were foliarly sprayed with ASM and were exposed to non-
stress (20/15°C day/night), heat stress (35/30°C), or drought conditions (by withholding
irrigation) in controlled-environment growth chambers. Exogenous ASM treatment
resulted in improved heat or drought tolerance, as demonstrated by higher overall turf
quality, relative water content, and chlorophyll content compared to the untreated control.
Clarke, B (2006) researched the effect of (ASM) against dollar spot when used as a
standalone treatment. The work was carried out on greens height Crenshaw bentgrass and
showed that when used alone Acibenzolar-S-methyl possessed significant efficacy vs dollar
spot.
Further work by Mr. Steve McDonald on Princeville creeping bentgrass in 2011
demonstrated a longer residual against dollar spot was achieved in conjunction with
chlorothalonil (Daconil Action®) compared to straight chlorothalonil (Daconil Ultrex®),
and in conjunction with improved turf quality.

Acibenzolar-S-methyl (ASM) plus chlorothalonil longevity and quality improvements cv
‘Princeville’
This improved efficacy is repeated against anthracnose as shown in 2010 by Kaminski, J.
Daconil Action®-treated annual bluegrass had anthracnose levels of less than 3%, better
than any other fungicide.
The effect of Daconil Action® on anthracnose control

Salicylic acid
Plants rich in SA and its derivatives, collectively termed salicylates, have been used for
medicinal purposes for millennia. Today, aspirin is one of the most widely used drugs in the
world. In addition to treating fever, swelling, pain, and inflammation, aspirin is used
prophylactically to reduce the risk of stroke, heart attack, and certain cancers.
Salicylic acid (SA) is a phenolic phytohormone and is found in plants with roles in plant
growth and development, photosynthesis, transpiration, ion uptake and transport. It is
involved in endogenous signaling against both biotic and abiotic stress, being an important
plant hormone that regulates many aspects of plant growth and development.
Salicylic acid or orthohydroxy benzoic acid is ubiquitously distributed plant growth
regulator (Raskin, 1992). Salicylic acid has positive effects on plant growth and
developmental processes [Senaratna et al, 2000). Research findings demonstrated its roles
in seed germination, glycolysis, flowering, fruit yield (Klessig and Malamy 1994),
photosynthetic rate, stomatal conductance (gs), and in transpiration (Khan et al, 2003).
Salicylic acid can modulate antioxidant defense system thereby decreasing oxidative stress
(Shirasu et al, 1997).
Photosynthesis, nitrogen metabolism, proline (Pro) metabolism, production of
glycinebetaine (GB), and plant-water relations in abiotic stress affected plants were
regulated by SA (Miura and Tada, 2014). SA application has also reportedly increaed heat
toelrance (Larkindale, 2002). Induction of defence-related genes and stress resistance in
biotic stressed plants have also been reported (Kumar, 2014).
SA is an effective SAR inducer, but its phytotoxicity precludes widespread use (Conrath et
al, 2015). While treating plants or suspension cells with high concentrations of SA or its
functional analogs directly induces defences, low concentrations elicit little to no response.
Following subsequent infection, however, defences are activated more rapidly and/or
strongly (Conrath et al, 2006). This phenomenon, termed priming, also occurs in systemic
leaves of plants exhibiting SAR.
Work by Wang et al (2010) studied the impact of SA pretreatment on photosynthesis was
evaluated in the leaves of young grapevines before heat stress (25°C), during heat stress
(43°C for 5 h), and through the following recovery period (25°C).Following heat treatment,
the recovery of SA-treated leaves was accelerated compared with the control (H2O-
treated) leaves
Comparative work looking at the efficacy of salicylic acid and Acibenzolar-S-methyl (ASM)
was carried out into Alternaria solani, which is a destructive pathogen to tomato crops
(Aslam et al, 2019). Foliar and seedling root dipping application of Bion and salicylic acid
not only reduced the disease severity but also enhanced the plant growth.

Germination
The role of SA in seed germination has been controversial as there are conflicting reports
suggesting that it can either inhibit germination or increase seed vigour. The reported
contradictory effects can be related to the SA concentrations employed. In A. thaliana, SA
concentrations >1 mM delay or even inhibit germination (Rajjou et al., 2006). In barley,
doses >0.250 mM SA inhibit seed germination (Xie et al., 2007), while maize germination is
completely inhibited by SA doses ranging from 3 mM to 5 mM (Guan and Scandalios, 1995).
SA’s effect as a negative regulator of seed germination is presumably due to an SA-induced
oxidative stress. In Arabidopsis plants treated with SA (1–5 mM), hydrogen peroxide
(H2O2) levels increase up to 3-fold as a result of increased activities of Cu, Zn-superoxide
dismutase and inactivation of the H2O2-degrading enzymes catalase and ascorbate
peroxidase (Rao et al., 1997).
Interestingly, when low doses are applied exogenously, SA significantly improves
Arabidopsis seed germination and seedling establishment under different abiotic stress
conditions (Rajjou et al., 2006; Alonso-Ramírez et al., 2009). Under salt stress (100–150
mM NaCl) only 50% of Arabidopsis seeds germinate, but in the presence of SA (0.05–0.5
mM) seed germination increases to 80%. Exogenous application of SA also partially
reverses the inhibitory effect of oxidative (0.5 mM paraquat) and heat stress (50 °C for 3 h)
on seed germination (Alonso-Ramírez et al., 2009)
Vegetative Growth
The effect of exogenous SA on growth depends on the plant species, developmental stage,
and the SA concentrations tested. Growth-stimulating effects of SA have been reported in
soybean (Gutiérrez-Coronado et al., 1998), wheat (Shakirova et al., 2003), maize (Gunes et
al., 2007), and chamomile (Kovácik et al., 2009). In soybean plants treated with 10 nM, 100
μM, and up to 10 mM SA, shoot and root growth increase ∼20% and 45%, respectively, 7 d
after application. Wheat seedlings treated with 50 μM SA develop larger ears, and
enhanced cell division is observed within the apical meristem of seedling roots (Shakirova
et al., 2003).
Heat Stress
The ﬁrst paper to demonstrate the effect of SA on heat tolerance showed that the heat
tolerance of mustard plants was improved by spraying with SA (Dat and others 1998a).
This effect was concentration-dependent, as SA exhibited a protective effect only at low
concentrations (0.01–0.1mM). SA also enhanced the thermotolerance of tobacco plants
when applied at low concentration (10 lmol/L), whereas at ten times this concentration it
had no protective effect against heat stress(Dat and others 2000). Not only heat
acclimation but also the application of exogenous SA improved the survival of pea plants
after heat stress. In cucumber plants (Cucumis sativa L.), foliar spraying with 1 mM SA
induced heat tolerance and plants may also tolerate elevated temperatures without heat
acclimation or any chemical treatment. This phenomenon is called basal thermotolerance.

Plants subjected to mild heat stress may transiently acquire tolerance to previously lethal
high temperatures (that is, heat acclimatization or acquiredthermotolerance) (Clarke and
others 2004). Heat acclimation was also followed by a transient increase in the endogenous
SA level in pea (Pisum sativum L.) plants, whereas inhibitors of SA biosynthesis reduced the
tolerance of the plants to heat stress (Pan and others 2006). Experiments on grapevine
(Vitis vinifera L.) also showed a sharp increase in the SA level at the beginning of heat
acclimation, whereas exogenous SA also induced a level of thermotolerance similar to that
of heat acclimation (Wang and Li 2006). This induction of thermotolerance was related to
changes in the antioxidant enzyme activities.
Turf specific research
The level of SA was shown to increase slightly after the ﬁrst hour of heat stress in creeping
bentgrass (Agrostis stolonifera) (Larkindale and Huang 2005).
Work was carried out on perennial ryegrass by Shahgholi et al, 2013 examining the
interaction between Trinexapac ethyl and salicylic acid. Treatment of 0.27 g of salicylic acid
had the maximum height compared with other treatments which showed significant
difference from control treatment at 5% level. Trinexapac ethyl with concentrations of 0.8
and 1.2 ml/m2 and salicylic acid with concentrations of 0.27 and 0.54 g/ m2 increased
colour quality and chlorophyll content.
He et al 2005 examined the effects of SA at different concentrations (0, 0.1, 0.25, 0.5, 1, and
1.5 mmol) on heat tolerance of Kentucky bluegrass exposed to 46°C for 72 h in a growth
chamber. Among SA concentrations, 0.25 mmol was most effective in enhancing heat
tolerance in Kentucky bluegrass, which was manifested by improved regrowth potential
following heat stress of 72 h and maintenance of leaf water content at 77% during the 12-h
stress period similar to that under normal temperature conditions.
Hosseini, Kafi and Arghavani (2016) looked at the effect of salicylic acid on physiological
characteristics of Lolium grass (Lolium perenne cv. ‘Numan’) under drought stress. Salicylic
acid foliar application at 0.75 and 1.5 mm levels increased the content of chlorophyll a, b
and reduced electrolyte leakage, proline accumulation and antioxidant enzyme activity,
which suggested that salicylic acid can be used to reduce the negative impacts of drought
stress.
Trial Overview
A randomised block trial was marked out after using Edgar II for its design and layout. This
comprised 30 pots having a surface area of 20cm2 containing a depth of cm of a USGA
specification sand. These were placed in a grow tray. The randomized block trial initially
comprised 6 treatments with 5 replicates. These were seeded on 12th March 2020 with
perennial ryegrass (Lolium perenne cv. ‘Stellar 3G’) at an equivalent rate of 300Kg/ha.
Following this the treatments were applied one day following seeding on the 13th of March
2020. Repeat applications of all treatments apart from IBDU were made on 24th March
2020.

Treatments comprised: an untreated control, IBDU, Salicylic acid, Salicylic acid plus 6
benzylaminopurine, Vertmax Duo® and copper phthalocyanine green plus salicylic acid.
Product was applied using a hand held pump pack in an equivalent water volume of
600L/Ha (foliar application). The water source used was town water.
Table showing Treatments and Rates for Elicitor trial with Stellar 3G
Treatment Rate/m2 Rate ml/20cm2 pot Water volume L/Ha
0.1 0.0002 600
0.1 0.0002 600
0.1 0.0002 600
0.1 0.0002 600
- - 600
Product 1 (A)
Product 2 (B)
Vertmax Duo (C)
Product 3 (D)
Control (E)
IBDU (F) 30g 0.06g 600
Assessments were as follows:
1. Germination rate.
Following seeding a visual assessment of germination rate was carried out coupled with
digital image analysis.
2. Growth rate.
Growth rate was assessed by taking daily digital images and analysing these using ImageJ.
3. Root growth
Root length was measured by breaking up the cores and then measuring individual roots
using digital image analysis and then Image J with the GLORIA plugin.
Treatments were applied on the following dates (apart from IBDU): 13th March 2020
(pregermination), 25th March 2020, 1st April 2020.

Results
Pots were monitored regularly using digital image analysis in combination with Image J.
Images were taken regularly in both RAW and PNG format using a modified Canon
PowerShot SX260 HS with NDVI filter and an Olympus Stylus respectively. Statistical
analysis was carried out using RStudio.
Post seeding Treatment and germination
Germination and Seedling Length
0
5
10
15
20
25
30
35
40
45
50
0 4 5 6 7 8 9 12 15
MeanNumbergerminatedseeds
Days after seeding
Graph of mean number of germinated seeds
over time
E A C B D F

0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 4 5 6 7 8 9 12 15
MeanLengthgerminatedseeds
Days after seeding
Graph of mean Shoot length cm of
germinated seeds over time
E A C B D F

Analysis of Variance Model - Germination
Df Sum Sq Mean Sq F value Pr(>F)
Treatment 5 1069 213.7 6.342 0.0006937
Residuals 24 808.8 33.7 NA NA
• statistics:
MSerror Df Mean CV MSD
158.4 234 18.72 67.23 8.087
• parameters:
test name.t ntr StudentizedRange alpha
Tukey Treatment 6 4.064 0.05
• means:
Germinated std r Min Max Q25 Q50 Q75
A 17.75 14.13 40 0 45 3 21 26.25
B 20.38 10.83 40 4 52 12.75 17.5 25
C 35.02 15.14 40 11 66 23.5 33.5 45
D 17.5 9.597 40 0 36 10 17.5 25
E 14.65 15.32 40 0 53 0.75 9 28.25
F 7.025 8.801 40 0 33 0 3 10.5
• comparison:
• groups:
Germinated groups
C 35.02 a
B 20.38 b
A 17.75 b
D 17.5 b
E 14.65 bc
F 7.025 c

Analysis of Variance Model - Shoot length
Treatment 5 0.1004 0.02008 3.604 0.01425
Residuals 24 0.1337 0.005571 NA NA
• statistics:
0.005571 24 0.1005 74.26 0.146
• parameters:
• means:
Length std r Min Max Q25 Q50 Q75
A 0.1109 0.1025 5 0 0.207 0 0.161 0.1863
B 0.1188 0.04651 5 0.038 0.148 0.12 0.144 0.144
C 0.1945 0.07784 5 0.08925 0.29 0.146 0.2234 0.2237
D 0.1212 0.07561 5 0 0.196 0.1057 0.137 0.167
E 0.021 0.04696 5 0 0.105 0 0 0
F 0.0368 0.08229 5 0 0.184 0 0 0
• comparison:
• groups:
Length groups
C 0.1945 a
D 0.1212 ab
B 0.1188 ab
A 0.1109 ab
F 0.0368 b
E 0.021 b

Treatment 5 2315 463.1 5.329 0.001966
Residuals 24 2086 86.9 NA NA
• statistics:
86.9 24 12.97 71.89 18.23
• parameters:
• means:
A 14.2 14.55 5 1 35 1 12 22
B 14.6 6.542 5 7 25 13 13 15
C 28.8 9.96 5 15 42 25 29 33
D 14.2 8.927 5 1 23 10 16 21
E 5 9.11 5 0 21 0 0 4
F 1 2.236 5 0 5 0 0 0
• comparison:
• groups:
Germinated groups
C 28.8 a
B 14.6 ab
A 14.2 ab
D 14.2 ab
E 5 b
F 1 b

Analysis of Variance Model - Shoot Length
Treatment 5 0.1719 0.03438 5.992 0.0009845
Residuals 24 0.1377 0.005737 NA NA
• statistics:
0.005737 24 0.1418 53.43 0.1481
• parameters:
• means:
A 0.1535 0.09027 5 0 0.2385 0.169 0.171 0.189
B 0.1714 0.05725 5 0.1072 0.234 0.118 0.18 0.2177
C 0.2557 0.08705 5 0.1868 0.393 0.1936 0.215 0.2903
D 0.1802 0.05769 5 0.099 0.244 0.145 0.203 0.21
E 0.053 0.07295 5 0 0.143 0 0 0.122
F 0.0368 0.08229 5 0 0.184 0 0 0
• comparison:
• groups:
Length groups
C 0.2557 a
D 0.1802 ab
B 0.1714 ab
A 0.1535 ab
E 0.053 b
F 0.0368 b

Treatment 5 3092 618.3 4.785 0.003565
• statistics:
129.2 24 14.6 77.86 22.23
• parameters:
• means:
A 17.4 16.82 5 0 38 0 24 25
B 16 8.124 5 10 29 11 11 19
C 33 14.93 5 12 53 28 34 38
D 14.6 7.956 5 5 25 10 13 20
E 6 11.77 5 0 27 0 1 2
F 0.6 1.342 5 0 3 0 0 0
• comparison:
• groups:
Germinated groups
C 33 a
A 17.4 ab
B 16 ab
D 14.6 ab
E 6 b
F 0.6 b

Analysis of Variance Model – Shoot Growth
Treatment 5 0.6056 0.1211 8.276 0.0001168
Residuals 24 0.3512 0.01463 NA NA
• statistics:
0.01463 24 0.2206 54.85 0.2366
• parameters:
• means:
A 0.1708 0.164 5 0 0.3673 0 0.235 0.2515
B 0.3083 0.0767 5 0.2308 0.4355 0.2766 0.2898 0.309
C 0.39 0.1233 5 0.2663 0.52 0.27 0.3847 0.509
D 0.3625 0.1647 5 0.2336 0.623 0.2593 0.268 0.4288
E 0.06854 0.1001 5 0 0.2207 0 0 0.122
F 0.0232 0.05188 5 0 0.116 0 0 0
• comparison:
• groups:
Length groups
C 0.39 a
D 0.3625 a
B 0.3083 a
A 0.1708 ab
E 0.06854 b
F 0.0232 b

Treatment 5 2656 531.3 4.945 0.002983
• statistics:
107.4 24 15.1 68.64 20.27
• parameters:
• means:
A 16.8 14.11 5 1 33 3 22 25
B 17.2 8.167 5 11 31 12 14 18
C 32.6 13.32 5 12 45 27 38 41
D 13.2 5.805 5 5 19 10 14 18
E 9 12.71 5 0 31 1 5 8
F 1.8 2.49 5 0 6 0 1 2
• comparison:
• groups:
Germinated groups
C 32.6 a
B 17.2 ab
A 16.8 ab
D 13.2 ab
E 9 b
F 1.8 b

Treatment 5 0.6765 0.1353 3.468 0.01685
Residuals 24 0.9363 0.03901 NA NA
• statistics:
0.03901 24 0.3291 60.01 0.3862
• parameters:
• means:
A 0.267 0.2516 5 0 0.4968 0 0.3435 0.4949
B 0.4119 0.1779 5 0.2444 0.6767 0.2897 0.3431 0.5057
C 0.5289 0.1618 5 0.3098 0.7332 0.4342 0.5788 0.5885
D 0.4607 0.2155 5 0.2546 0.7501 0.2553 0.451 0.5923
E 0.2053 0.2372 5 0 0.5038 0 0.1105 0.412
F 0.101 0.101 5 0 0.2085 0 0.1015 0.195
• comparison:
• groups:
Length groups
C 0.5289 a
D 0.4607 ab
B 0.4119 ab
A 0.267 ab
E 0.2053 ab
F 0.101 b

Analysis of Variance Model – Germination
Treatment 5 2663 532.7 3.223 0.02292
• statistics:
165.3 24 20.73 62 25.14
• parameters:
• means:
A 20.4 16.36 5 3 42 5 25 27
B 22.6 10.01 5 15 40 17 20 21
C 39 15.25 5 19 60 31 42 43
D 16.8 8.106 5 6 26 12 17 23
E 18 16 5 1 40 5 17 27
F 7.6 8.325 5 1 22 3 6 6
• comparison:
• groups:
Germinated groups
C 39 a
B 22.6 ab
A 20.4 ab
E 18 ab
D 16.8 ab
F 7.6 b

Treatment 5 0.8127 0.1625 6.326 0.0007045
Residuals 24 0.6166 0.02569 NA NA
• statistics:
0.02569 24 0.4081 39.28 0.3135
• parameters:
• means:
A 0.4451 0.1628 5 0.196 0.5912 0.376 0.492 0.5704
B 0.4711 0.2043 5 0.257 0.7689 0.3554 0.3908 0.5834
C 0.6227 0.1381 5 0.5133 0.8636 0.5616 0.5851 0.5898
D 0.4987 0.1914 5 0.3153 0.7792 0.3231 0.5241 0.5517
E 0.3074 0.1592 5 0.1042 0.458 0.186 0.3326 0.456
F 0.1035 0.06957 5 0 0.1832 0.0745 0.1238 0.1358
• comparison:
• groups:
Length groups
C 0.6227 a
D 0.4987 ab
B 0.4711 ab
A 0.4451 ab
E 0.3074 bc
F 0.1035 c

Analysis of Variance Model – Germination
Treatment 5 2428 485.6 3.175 0.02437
• statistics:
152.9 24 21.83 56.64 24.18
• parameters:
• means:
A 20.2 15.16 5 3 41 8 23 26
B 22.2 11.65 5 16 43 17 17 18
C 39.6 16.61 5 19 61 29 39 50
D 20 8.093 5 9 28 14 24 25
E 19.8 12.7 5 6 34 10 17 32
F 9.2 7.05 5 3 21 6 6 10
• comparison:
• groups:
Germinated groups
C 39.6 a
B 22.2 ab
A 20.2 ab
D 20 ab
E 19.8 ab
F 9.2 b

Treatment 5 0.8961 0.1792 3.971 0.009135
• statistics:
0.04513 24 0.5439 39.06 0.4154
• parameters:
• means:
A 0.5934 0.2279 5 0.2041 0.7665 0.6144 0.6332 0.749
B 0.6383 0.1747 5 0.3997 0.8145 0.5846 0.5855 0.807
C 0.8072 0.2035 5 0.6025 1.098 0.645 0.7745 0.916
D 0.5706 0.2155 5 0.2971 0.814 0.3955 0.667 0.6792
E 0.3706 0.2944 5 0.1196 0.8328 0.1447 0.2805 0.4754
F 0.2835 0.1175 5 0.1375 0.3928 0.183 0.3175 0.3869
• comparison:
• groups:
Length groups
C 0.8072 a
B 0.6383 ab
A 0.5934 ab
D 0.5706 ab
E 0.3706 b
F 0.2835 b

Treatment 5 2196 439.2 2.466 0.06136
• statistics:
178.1 24 28.53 46.77 26.09
• parameters:
• means:
A 22.4 14.52 5 7 43 10 25 27
B 29.4 12.78 5 21 52 23 25 26
C 44.6 16.67 5 24 60 30 50 59
D 25.2 10.33 5 11 36 18 30 31
E 32 15.05 5 11 53 28 34 34
F 17.6 9.127 5 10 33 12 15 18
• comparison:
• groups:
Germinated groups
C 44.6 a
E 32 ab
B 29.4 ab
D 25.2 ab
A 22.4 ab
F 17.6 b

Treatment 5 1.502 0.3004 4.48 0.00503
• statistics:
0.06705 24 0.7741 33.45 0.5064
• parameters:
• means:
A 0.7705 0.3314 5 0.3855 1.061 0.4352 0.9537 1.017
B 0.8397 0.1917 5 0.6961 1.161 0.7302 0.739 0.8721
C 1.144 0.1821 5 0.94 1.342 0.9831 1.151 1.305
D 0.8562 0.3602 5 0.3264 1.224 0.722 0.8609 1.148
E 0.6174 0.2862 5 0.1962 0.8311 0.4415 0.7999 0.8184
F 0.4165 0.1043 5 0.2776 0.5586 0.3768 0.4044 0.4649
• comparison:
• groups:
Length groups
C 1.144 a
D 0.8562 ab
B 0.8397 ab
A 0.7705 ab
E 0.6174 b
F 0.4165 b

Treatment 5 2117 423.3 3.281 0.02131
Residuals 24 3097 129 NA NA
pander(outHSD)
## Warning in pander.default(outHSD): No pander.method for "group", reverting to
## default.
• statistics:
129 24 28.57 39.76 22.21
• parameters:
• means:
A 22.4 15.09 5 7 45 11 21 28
B 30.8 9.524 5 21 46 25 30 32
C 45 14.34 5 29 66 35 45 50
D 28 7.649 5 15 34 28 30 33
E 27 11.98 5 12 43 19 29 32
F 18.2 6.943 5 10 28 15 16 22
• comparison:
• groups:
Germinated groups
C 45 a
B 30.8 ab
D 28 ab
E 27 ab
A 22.4 b
F 18.2 b

Treatment 5 1.179 0.2358 4.081 0.008007
• statistics:
0.05778 24 0.9548 25.18 0.4701
• parameters:
• means:
A 0.9894 0.28 5 0.6071 1.325 0.854 0.981 1.18
B 0.974 0.175 5 0.836 1.268 0.845 0.958 0.963
C 1.286 0.1774 5 1.062 1.554 1.229 1.275 1.309
D 1.022 0.3488 5 0.502 1.396 0.9 1.042 1.269
E 0.8242 0.2653 5 0.484 1.092 0.64 0.836 1.069
F 0.6336 0.1193 5 0.532 0.786 0.551 0.56 0.739
• comparison:
• groups:
Length groups
C 1.286 a
D 1.022 ab
A 0.9894 ab
B 0.974 ab
E 0.8242 ab
F 0.6336 b

Analysis of Variance Model – area of roots
Treatment 5 121 24.2 7.29 9.585e-06
• statistics:
MSerror Df Mean CV
3.32 87 2.042 89.25
• parameters:
• means:
area std r Min Max Q25 Q50 Q75
A 1.309 1.182 8 0.2882 3.86 0.6042 0.802 1.638
B 1.965 1.736 24 0.01582 6.616 0.6991 1.34 2.611
C 4.305 2.678 17 1.272 9.61 2.165 3.34 5.335
D 1.794 1.899 19 0.05719 6.175 0.3806 0.7101 3.711
E 1.106 1.164 20 0.201 5.623 0.603 0.8423 1.067
F 0.5701 1.047 5 0.0059 2.432 0.02699 0.09301 0.2922
• comparison:
• groups:
area groups
C 4.305 a
B 1.965 b
D 1.794 b
A 1.309 b
E 1.106 b
F 0.5701 b

Analysis of Variance Model - depth
Treatment 5 16.24 3.248 4.035 0.002434
• statistics:
MSerror Df Mean CV
0.805 87 1.617 55.48
• parameters:
• means:
depth std r Min Max Q25 Q50 Q75
A 1.49 0.6057 8 0.4733 2.4 1.233 1.587 1.765
B 1.616 0.7112 24 0.5 3.74 1.19 1.57 1.955
C 2.294 1.01 17 0.8667 3.687 1.76 1.947 3.48
D 1.745 1.169 19 0.2867 3.727 0.64 1.633 2.5
E 1.218 0.8225 20 0.22 3.437 0.7183 0.9467 1.458
F 0.6347 0.7193 5 0.1533 1.9 0.2667 0.34 0.5133
• comparison:
• groups:
depth groups
C 2.294 a
D 1.745 ab
B 1.616 ab
A 1.49 ab
E 1.218 b
F 0.6347 b

Analysis of Variance Model – width of roots
Treatment 5 17.83 3.566 5.818 0.0001108
• statistics:
MSerror Df Mean CV
0.6129 87 1.315 59.54
• parameters:
• means:
width std r Min Max Q25 Q50 Q75
A 1.025 0.6111 8 0.21 1.837 0.44 1.15 1.39
B 1.373 0.9452 24 0.02333 3.417 0.6483 1.213 2.05
C 2.146 0.8404 17 0.69 3.203 1.57 2.27 2.863
D 1.1 0.8315 19 0.1033 2.657 0.4667 0.79 1.697
E 1.055 0.5269 20 0.3233 2.03 0.6983 0.98 1.213
F 0.5273 0.5336 5 0.03 1.397 0.2233 0.35 0.6367
• comparison:
• groups:
width groups
C 2.146 a
B 1.373 b
D 1.1 b
E 1.055 b
A 1.025 b
F 0.5273 b

Root Growth after 26 Days
0.5 1 1.5 2 2.5 3 3.5
A
B
C
D
E
F
Mean Length in cm
Treatment
Mean Root Length after 26 Days
94.59%
74.02%
122.15%
101.37%
30.00%
25.00% 45.00% 65.00% 85.00% 105.00% 125.00% 145.00%
A
B
C
D
F
Percentage of control
Treatment
Percentage change in root Growth
compared to Control

Analysis of Variance Model – Root Length after 26 days and after 24 hours at 42°C
Treatment 5 196.3 39.26 20.58 2.919e-19
• statistics:
MSerror Df Mean CV
1.907 730 2.378 58.08
• parameters:
• means:
A 2.272 1.432 83 0.41 5.905 1.073 1.964 3.428
B 1.778 1.069 103 0.369 6.886 1.058 1.551 2.232
C 2.934 1.362 208 0.458 6.186 1.827 2.974 4.02
D 2.435 1.571 111 0.241 6.21 1.148 1.952 3.72
E 2.402 1.501 197 0.218 6.325 1.096 2.159 3.478
F 0.7205 0.5522 34 0.136 2.72 0.4027 0.495 1.093
• comparison:
• groups:
Length groups
C 2.934 a
D 2.435 b
E 2.402 b
A 2.272 bc
B 1.778 c
F 0.7205 d

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